{"id":"W2900510420","doi":"10.1109/bdva.2018.8534019","title":"Multiple Workspaces in Visual Analytics","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Workspace; Computer science; Visual analytics; Visualization; Exploratory analysis; Analytics; Human–computer interaction; Process (computing); Data visualization; Exploratory research; Work (physics); Interactive visual analysis; Path (computing); Data science; Data mining; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001464764,0.00006077347,0.0000756931,0.0001354902,0.00003895824,0.0001461217,0.000404226,0.00002937158,0.00008520157],"category_scores_gemma":[0.00007740966,0.00005198391,0.00001787465,0.0007655885,0.00004313392,0.0003422015,0.0001695364,0.00003991118,0.000257928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001424063,"about_ca_system_score_gemma":0.00002733175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003237112,"about_ca_topic_score_gemma":0.0004722437,"domain_scores_codex":[0.9993647,0.00002124413,0.0001349161,0.0001857044,0.0001372232,0.0001561922],"domain_scores_gemma":[0.9995813,0.00004324306,0.00002911641,0.0002344514,0.00005729355,0.00005457146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001107405,0.0006351263,0.2535969,0.00001579689,0.00003516902,0.00003407599,0.001798365,0.0003997371,0.000462147,0.6292403,0.05285808,0.06091325],"study_design_scores_gemma":[0.000191516,0.00003845501,0.004428362,0.000006957659,0.00000105375,9.018596e-7,0.00006069392,0.979508,0.0007658331,0.0005404999,0.01436356,0.00009418527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009037778,0.000008067288,0.9817063,0.0005196175,0.0001375012,0.00003508382,6.560286e-7,0.0001085506,0.008446437],"genre_scores_gemma":[0.9726694,0.000008128793,0.02433923,0.0009849003,0.00006800861,7.867492e-7,0.000003897581,0.000003547262,0.001922104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9791083,"threshold_uncertainty_score":0.3315229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02759077134307323,"score_gpt":0.3255944979311638,"score_spread":0.2980037265880905,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}